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            <name>Title</name>
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    <name>Article</name>
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          <name>Title</name>
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              <text>Offline Handwritten Character and Numeral Recognition: A Kernel-Based Approach</text>
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          <name>Subject</name>
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              <text>Fast Discrete Curvelet Translation (FCDT); Gaussian; Kernel-PCA; Optical Character Recognition; Principal Component Analysis; Probabilistic Neural Network (PNN)</text>
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              <text>Automatic character recognition for the handwritten Indic script is a challenging area for research in the field of pattern recognition. Although a great amount of research work has been reported, all the state-of-the-art methods are limited with optimal features. This article aims to suggest a well-defined recognition model which harnessed upon handwritten Odia characters and numerals by implementing a novel process of decomposition in terms of 3rd level fast discrete curvelet transform (FDCT) to get higher dimension feature vector. After that, kernel-principal component analysis (K-PCA) is considered to obtain optimal features from FDCT feature. Finally, the classification is performed by using probabilistic neural network (PNN) on a handwritten Odia character and numeral dataset from both NIT Rourkela and IIT Bhubaneswar. The outcome of the proposed scheme performs better compared to existing models with optimized Gaussian kernel-based feature sets. Copyright  2022, IGI Global.</text>
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          <name>Creator</name>
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              <text>Sethy A.; Patra P.K.; Nayak S.R.; Poonia R.C.</text>
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          <name>Source</name>
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              <text>International Journal of Social Ecology and Sustainable Development, Vol-13, No. 1</text>
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          <name>Publisher</name>
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              <text>IGI Global</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.4018/IJSESD.295087" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/IJSESD.295087&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147152380&amp;amp;doi=10.4018%2FIJSESD.295087&amp;amp;partnerID=40&amp;amp;md5=626585ba2dd6c63070020a2ce93e58d8" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147152380&amp;amp;doi=10.4018%2fIJSESD.295087&amp;amp;partnerID=40&amp;amp;md5=626585ba2dd6c63070020a2ce93e58d8&lt;/a&gt;</text>
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          <name>Rights</name>
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            <elementText elementTextId="110216">
              <text>Restricted Access</text>
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          <name>Relation</name>
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              <text>ISSN: 19478402</text>
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          <name>Format</name>
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              <text>Online</text>
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          <name>Language</name>
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              <text>English</text>
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              <text>Sethy A., Department of Computer Science and Engineering, College of Engineering and Technology, BBSR, India; Patra P.K., Department of Computer Science and Engineering, College of Engineering and Technology, BBSR, India; Nayak S.R., Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, India; Poonia R.C., Department of Computer Science, CHRIST University (Deemed), Bangalore, India</text>
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